https://github.com/jhrcook/statistical-rethinking
Notes on Statistical Rethinking: A Bayesian Course with Examples in R and Stan
https://github.com/jhrcook/statistical-rethinking
bayesian bayesian-statistics r rstats statistical-rethinking statistics
Last synced: about 2 months ago
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Notes on Statistical Rethinking: A Bayesian Course with Examples in R and Stan
- Host: GitHub
- URL: https://github.com/jhrcook/statistical-rethinking
- Owner: jhrcook
- Created: 2020-04-27T11:59:03.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2020-07-03T19:42:56.000Z (almost 5 years ago)
- Last Synced: 2025-03-23T22:25:35.091Z (3 months ago)
- Topics: bayesian, bayesian-statistics, r, rstats, statistical-rethinking, statistics
- Language: R
- Homepage: https://xcelab.net/rm/statistical-rethinking/
- Size: 118 MB
- Stars: 4
- Watchers: 1
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
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README
---
output: github_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# Notes on *Statistical Rethinking: A Bayesian Course with Examples in R and Stan*
The first two chapters of the 2nd edition of this book are available as a [PDF](statisticalrethinking2_chapters1and2.pdf) for free.
The rest of the book I used the first edition as it is available through my schools library.
## Introduction
This book is an introduction to Bayesian statistics, focussing on providing an applicable education in R.
This repository contains my notes; these notes are not a thorough recapitulation of the book, but instead acting as a combination of a reference and a playground for myself.
These notes have been compiled into a simple static website for ease of reference and searching.
[](https://statistical-rethinking-notes.netlify.app)
## Setting-up
This course includes an R packages called 'rethinking']().
It can be installed as follows.
```r
# Dependencies
install.packages(c("coda", "mvtnorm", "devtools", "loo", "dagitty"))
# Course package
devtools::install_github("rmcelreath/rethinking")
```
## Chapter Notes
[Chapter 1. The Golem of Prague](ch1_the-golem-of-prague.md)
[Chapter 2. Small Worlds and Large Worlds](ch2_small-worlds-and-large-worlds.md)
[Chapter 3. Sampling the Imaginary](ch3_sampling-the-imaginary.md)
[Chapter 4. Linear Models](ch4_linear-models.md)
[Chapter 5. Multivariate Linear Models](ch5_multivariate-linear-models.md)
[Chapter 6. Overfitting, Regularization, and Information Criteria](ch6_overfitting-regularization-and-information-criteria.md)
[Chapter 7. Interactions](ch7_interactions.md)
[Chapter 8. Markov Chain Monte Carlo](ch8_markov-chain-monte-carlo.md)
[Chapter 9. Big Entropy and the Generalized Linear Model](ch9_big-entropy-and-the-generalized-linear-model.md)
[Chapter 10. Counting and Classification](ch10_counting-and-classification.md)
[Chapter 11. Monsters and Mixtures](ch11_monsters-and-mixtures.md)
[Chapter 12. Multilevel Models](ch12_multilevel-models.md)
[Chapter 13. Adventures in Covariance](ch13_adventures-in-covariance.md)
[Chapter 14. Missing Data and Other Opportunities](ch14_missing-data-and-other-opportunities.md)
---
## Other R packages for Bayes
Below are some of the common packages for using Baysian statistics in R.
The purpose of this collection is to serve as a reference for future work.
As I work through their vignettes (and possible other associated tutorals/articles), the markdown files will be linked below.
**['rstanarm'](https://mc-stan.org/rstanarm/index.html)**
- [my notes](bayes-packages/rstanarm.md)
**['brms'](https://paul-buerkner.github.io/brms/)**
**['ggmcmc'](https://cran.r-project.org/web/packages/ggmcmc/index.html)**
**['tidybayes'](http://mjskay.github.io/tidybayes)**
- [my notes](bayes-packages/tidybayes_vignettes.md)
**['bayetestR'](https://easystats.github.io/bayestestR/)** (part of the 'easystats' suite of packages)